Java examples for Big Data:Hadoop
Generates the sampled split points, launches the job, and waits for it to finish.
/**//from w w w. j a va 2 s.co m * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.hadoop.examples.terasort; import java.io.DataInputStream; import java.io.IOException; import java.io.PrintStream; import java.net.URI; import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.apache.hadoop.conf.Configurable; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.JobContext; import org.apache.hadoop.mapreduce.MRJobConfig; import org.apache.hadoop.mapreduce.Partitioner; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; /** * Generates the sampled split points, launches the job, and waits for it to * finish. * <p> * To run the program: * <b>bin/hadoop jar hadoop-*-examples.jar terasort in-dir out-dir</b> */ public class TeraSort extends Configured implements Tool { private static final Log LOG = LogFactory.getLog(TeraSort.class); static String SIMPLE_PARTITIONER = "mapreduce.terasort.simplepartitioner"; static String OUTPUT_REPLICATION = "mapreduce.terasort.output.replication"; /** * A partitioner that splits text keys into roughly equal partitions * in a global sorted order. */ static class TotalOrderPartitioner extends Partitioner<Text, Text> implements Configurable { private TrieNode trie; private Text[] splitPoints; private Configuration conf; /** * A generic trie node */ static abstract class TrieNode { private int level; TrieNode(int level) { this.level = level; } abstract int findPartition(Text key); abstract void print(PrintStream strm) throws IOException; int getLevel() { return level; } } /** * An inner trie node that contains 256 children based on the next * character. */ static class InnerTrieNode extends TrieNode { private TrieNode[] child = new TrieNode[256]; InnerTrieNode(int level) { super(level); } int findPartition(Text key) { int level = getLevel(); if (key.getLength() <= level) { return child[0].findPartition(key); } return child[key.getBytes()[level] & 0xff] .findPartition(key); } void setChild(int idx, TrieNode child) { this.child[idx] = child; } void print(PrintStream strm) throws IOException { for (int ch = 0; ch < 256; ++ch) { for (int i = 0; i < 2 * getLevel(); ++i) { strm.print(' '); } strm.print(ch); strm.println(" ->"); if (child[ch] != null) { child[ch].print(strm); } } } } /** * A leaf trie node that does string compares to figure out where the given * key belongs between lower..upper. */ static class LeafTrieNode extends TrieNode { int lower; int upper; Text[] splitPoints; LeafTrieNode(int level, Text[] splitPoints, int lower, int upper) { super(level); this.splitPoints = splitPoints; this.lower = lower; this.upper = upper; } int findPartition(Text key) { for (int i = lower; i < upper; ++i) { if (splitPoints[i].compareTo(key) > 0) { return i; } } return upper; } void print(PrintStream strm) throws IOException { for (int i = 0; i < 2 * getLevel(); ++i) { strm.print(' '); } strm.print(lower); strm.print(", "); strm.println(upper); } } /** * Read the cut points from the given sequence file. * @param fs the file system * @param p the path to read * @param job the job config * @return the strings to split the partitions on * @throws IOException */ private static Text[] readPartitions(FileSystem fs, Path p, Configuration conf) throws IOException { int reduces = conf.getInt(MRJobConfig.NUM_REDUCES, 1); Text[] result = new Text[reduces - 1]; DataInputStream reader = fs.open(p); for (int i = 0; i < reduces - 1; ++i) { result[i] = new Text(); result[i].readFields(reader); } reader.close(); return result; } /** * Given a sorted set of cut points, build a trie that will find the correct * partition quickly. * @param splits the list of cut points * @param lower the lower bound of partitions 0..numPartitions-1 * @param upper the upper bound of partitions 0..numPartitions-1 * @param prefix the prefix that we have already checked against * @param maxDepth the maximum depth we will build a trie for * @return the trie node that will divide the splits correctly */ private static TrieNode buildTrie(Text[] splits, int lower, int upper, Text prefix, int maxDepth) { int depth = prefix.getLength(); if (depth >= maxDepth || lower == upper) { return new LeafTrieNode(depth, splits, lower, upper); } InnerTrieNode result = new InnerTrieNode(depth); Text trial = new Text(prefix); // append an extra byte on to the prefix trial.append(new byte[1], 0, 1); int currentBound = lower; for (int ch = 0; ch < 255; ++ch) { trial.getBytes()[depth] = (byte) (ch + 1); lower = currentBound; while (currentBound < upper) { if (splits[currentBound].compareTo(trial) >= 0) { break; } currentBound += 1; } trial.getBytes()[depth] = (byte) ch; result.child[ch] = buildTrie(splits, lower, currentBound, trial, maxDepth); } // pick up the rest trial.getBytes()[depth] = (byte) 255; result.child[255] = buildTrie(splits, currentBound, upper, trial, maxDepth); return result; } public void setConf(Configuration conf) { try { FileSystem fs = FileSystem.getLocal(conf); this.conf = conf; Path partFile = new Path(TeraInputFormat.PARTITION_FILENAME); splitPoints = readPartitions(fs, partFile, conf); trie = buildTrie(splitPoints, 0, splitPoints.length, new Text(), 2); } catch (IOException ie) { throw new IllegalArgumentException( "can't read partitions file", ie); } } public Configuration getConf() { return conf; } public TotalOrderPartitioner() { } public int getPartition(Text key, Text value, int numPartitions) { return trie.findPartition(key); } } /** * A total order partitioner that assigns keys based on their first * PREFIX_LENGTH bytes, assuming a flat distribution. */ public static class SimplePartitioner extends Partitioner<Text, Text> implements Configurable { int prefixesPerReduce; private static final int PREFIX_LENGTH = 3; private Configuration conf = null; public void setConf(Configuration conf) { this.conf = conf; prefixesPerReduce = (int) Math.ceil((1 << (8 * PREFIX_LENGTH)) / (float) conf.getInt(MRJobConfig.NUM_REDUCES, 1)); } public Configuration getConf() { return conf; } @Override public int getPartition(Text key, Text value, int numPartitions) { byte[] bytes = key.getBytes(); int len = Math.min(PREFIX_LENGTH, key.getLength()); int prefix = 0; for (int i = 0; i < len; ++i) { prefix = (prefix << 8) | (0xff & bytes[i]); } return prefix / prefixesPerReduce; } } public static boolean getUseSimplePartitioner(JobContext job) { return job.getConfiguration().getBoolean(SIMPLE_PARTITIONER, false); } public static void setUseSimplePartitioner(Job job, boolean value) { job.getConfiguration().setBoolean(SIMPLE_PARTITIONER, value); } public static int getOutputReplication(JobContext job) { return job.getConfiguration().getInt(OUTPUT_REPLICATION, 1); } public static void setOutputReplication(Job job, int value) { job.getConfiguration().setInt(OUTPUT_REPLICATION, value); } public int run(String[] args) throws Exception { LOG.info("starting"); Job job = Job.getInstance(getConf()); Path inputDir = new Path(args[0]); Path outputDir = new Path(args[1]); boolean useSimplePartitioner = getUseSimplePartitioner(job); TeraInputFormat.setInputPaths(job, inputDir); FileOutputFormat.setOutputPath(job, outputDir); job.setJobName("TeraSort"); job.setJarByClass(TeraSort.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(Text.class); job.setInputFormatClass(TeraInputFormat.class); job.setOutputFormatClass(TeraOutputFormat.class); if (useSimplePartitioner) { job.setPartitionerClass(SimplePartitioner.class); } else { long start = System.currentTimeMillis(); Path partitionFile = new Path(outputDir, TeraInputFormat.PARTITION_FILENAME); URI partitionUri = new URI(partitionFile.toString() + "#" + TeraInputFormat.PARTITION_FILENAME); try { TeraInputFormat.writePartitionFile(job, partitionFile); } catch (Throwable e) { LOG.error(e.getMessage()); return -1; } job.addCacheFile(partitionUri); long end = System.currentTimeMillis(); System.out.println("Spent " + (end - start) + "ms computing partitions."); job.setPartitionerClass(TotalOrderPartitioner.class); } job.getConfiguration().setInt("dfs.replication", getOutputReplication(job)); TeraOutputFormat.setFinalSync(job, true); int ret = job.waitForCompletion(true) ? 0 : 1; LOG.info("done"); return ret; } public static void main(String[] args) throws Exception { int res = ToolRunner.run(new Configuration(), new TeraSort(), args); System.exit(res); } }